Dynamic Models with Regime-Switching

Intensive longitudinal data have become increasingly prevalent in various scientific disciplines. Many such data sets are noisy, multivariate, and multi-subject in nature. The change functions may also be continuous, or continuous but interspersed with periods of discontinuities (i.e., showing regime switches). The package 'dynr' (Dynamic Modeling in R) is an R package that implements a set of computationally efficient algorithms for handling a broad class of linear and nonlinear discrete- and continuous-time models with regime-switching properties under the constraint of linear Gaussian measurement functions. The discrete-time models can generally take on the form of a state-space or difference equation model. The continuous-time models are generally expressed as a set of ordinary or stochastic differential equations. All estimation and computations are performed in C, but users are provided with the option to specify the model of interest via a set of simple and easy-to-learn model specification functions in R. Model fitting can be performed using single-subject time series data or multiple-subject longitudinal data. Ou, Hunter, & Chow (2019) provided a detailed introduction to the interface and more information on the algorithms.

README

This README file documents the steps necessary to get dynr cooking. That was the first of many food-based puns. It will not be the last.

Who is this repository for?

This repository is primarily for developers. If you're not currently on the development team but would like to be, please contact Sy-Miin Chow at Pennsylvania State University. You will need

• Good computer programming skills (R and C preferably)
• Decent mathematical ability
• Knowledge of or interest in dynamical systems
• Some exposure to statistical methods

If you're not a developer and just want to install dynr to run your models, please see the CRAN page including the vignette with installation guidelines.

How do I get set up?

Windows People

• Summary of set up
• Configuration
• Dependencies
• Database configuration
• How to run tests
• Deployment instructions

Mac People

• Summary of set up
• Configuration
• Dependencies
• Database configuration
• How to run tests
• Deployment instructions

Contribution guidelines

• Writing tests
• Code review
• Other guidelines

We primarily use a centralized workflow in git. Occasionally, we employ a feature branch style for larger features that may break the master branch for extended periods of time.

Please follow these basic guidelines when writing commit messages.

1. Separate subject from body with a blank line
2. Limit the subject line to 50 characters
3. Capitalize the subject line
4. Do not end the subject line with a period
5. Use the imperative mood in the subject line
6. Wrap the body at 72 characters
7. Use the body to explain what and why, not how

We use win-builder to help test the repository prior to submitting a new release to CRAN.

A Note to developers: there is a bug in roxygen2 such that the latest version will not build our documentation. It is a known issue that will be resolved soon. In the meantime, use an older version of the package. Install it with devtools::install_version(package = 'roxygen2',version = '5.0.1', repos = c(CRAN = "https://cran.rstudio.com"))

Who do I talk to?

• Michael D. Hunter is the Repo owner and admin
• Sy-Miin Chow is the principle investigator on the grant that funds dynr
• Other members of the development team include but are not limited to Lu Ou, Meng Chen, Linying Ji, Hui-Ju Hung, and Yanling Li

Contact the Repo owner to obtain write permission to this repository.